How to manage application performance
Application performance refers to the responsiveness, reliability, and scalability of an application. When an application takes too long to load, is unavailable, or slows as more people use it, users quickly become frustrated and look for alternatives. Steps to improving application performance include optimizing code and databases, setting up effective load balancing, optimizing for availability to minimize downtime, using a content delivery network (CDN), and architecting applications for efficiency.
Customers and employees alike expect software to respond in milliseconds. An application’s performance determines whether these expectations are met or not. Applications powered by artificial intelligence (AI) raise the bar for performance. They are supposed to provide dynamic, personalized experiences for customers and improve employee decision-making, but if they fail to deliver fast responses to user input, their benefits tend to dissipate.
Application performance management (APM)
Application performance management (APM) refers to the set of practices and technologies that track and enhance application performance. "APM" as an acronym can also refer to application performance monitoring, a concept that most in the industry now refer to as "observability."
What are the consequences of poor application performance?
Poor performance for customer-facing applications, like websites and mobile apps, affects:
Revenue: If an ecommerce site is slow, visitors buy from competitors and spend their money elsewhere.
Customer experience and brand reputation: When a website gains a reputation for being slow or unreliable, customers view the brand the same way.
Competitive advantage and market share: As slow experiences compel customers to leave bad reviews and move to faster sites and mobile apps, a business's competitive advantage erodes.
For internal software, poor performance impacts employee productivity and satisfaction.
Reduced productivity and efficiency: When office productivity applications are slow or offline, key internal processes come to a halt. If that software is unresponsive or unavailable, organizations lose hours and days of work.
Increased frustration: Ensuring employees have positive experiences with the tools they use is crucial for maintaining satisfaction. Internal websites for payroll, benefits, or HR that load slowly diminish employee morale.
See Why does site speed matter? to learn more.
What are the causes of application performance issues?
Causes range from the physical distance between users and data centers to unoptimized code. These causes can be divided into network / infrastructure factors and internal application factors.
Network and infrastructure factors affecting application performance
Enterprise networks and infrastructure play key roles in performance. Several factors affect latency, bandwidth, and congestion, including:
Physical distance: When users are far from the data centers hosting applications, inputs and responses take longer to reach their destinations. Even with fast Internet connections, a video conferencing app hosted in a centralized data center introduces latency for participants on different continents. Organizations can reduce the latency caused by the distance between users and data centers by using a CDN to cache content on distributed edge servers close to users.
Undercapacity and inefficient routing: Insufficient networks restrict how much data can move at once. A lack of bandwidth and throughput increases queueing, delays, and drops. Suboptimal network routing or asymmetric paths add hops and processing delays, which increase response times. Smart routing can help eliminate these issues.
**Infrastructure resource allocation:**The compute, memory, or storage capacity IT teams allot to each application affects speed and reliability. Server health checks, redundancy, load balancing, and other availability techniques are part of ensuring applications have sufficient resources.
Internal software factors affecting application performance
Internal factors — involving how developers code and deploy applications — can affect performance. These include:
Unoptimized code: When developer teams do not optimize code — or they over-use AI-assisted vibe coding — they can degrade application performance. Unoptimized code or an excessive reliance on third-party scripts introduces inefficiencies, including redundant computations and poor resource use. Development teams should adopt standards for simplifying, minifying, and reducing code. Reducing resource requests decreases network overhead and improves performance.
**Misconfigured servers:**Misconfigured servers increase latency and cause outages that degrade application performance. These misconfigurations include incorrect settings in configuration files that dictate how servers handle requests, databases, and resources. Test servers to ensure they perform as expected.
**Suboptimal load balancing:**Uneven workload distribution across server pools results in slower response times, resource waste, and outages under high demand. Sometimes this occurs due to a reliance on static load balancing when a more dynamic approach should be used instead (see Types of load balancing).
Legacy applications: Outdated software introduces architectural bottlenecks, resource inefficiencies, and integration overhead. By contrast, cloud-native architectures like serverless computing allow organizations to shift from the rigid monolithic designs of legacy software to flexible, scalable applications that perform better.
**Monitoring gaps:**Gaps in application monitoring prevent IT teams from identifying and addressing performance issues early. These gaps may occur in complex environments with microservices or cloud dependencies. (See What is observability?)
How to boost application performance
Improving performance through application modernization prepares your organization to capitalize on AI, which delivers revenue and efficiency benefits. According to the 2026 Cloudflare App Innovation Report, organizations that modernize applications are three times more likely to see ROI from AI investments compared to companies that do not. Likewise, 93% of leaders cite updating software as the most important factor in boosting their company’s AI capabilities.
Cloudflare offers a range of solutions to improve application performance and assist with modernization. For example, the Cloudflare Developer Platform lets development teams deploy serverless code instantly across the globe to increase performance, reliability, and scale. The global Cloudflare network and CDN platform — with caching, image optimization, smart routing, and load balancing included — reduce application latency and improve load times. Using the Cloudflare network with Workers AI lets developers run AI-powered applications at the edge, close to users, giving them the responsive experiences they expect.
FAQs
What is application performance?
Application performance encompasses how quickly an application responds, how reliable it is, and how well it scales. When software takes too long to load or becomes unavailable, users often experience frustration and seek alternative options.
What is application performance management (APM)?
Application performance management involves the technologies and practices organizations use to track and enhance how their software runs.
How does poor application performance impact a business?
For customer-facing software, slow response times lead to lost revenue, damaged brand reputation, and eroded competitive advantage. For internal tools, poor performance halts crucial processes, reduces efficiency, and lowers employee morale.
Why is updating legacy applications important for artificial intelligence (AI)?
Modernizing software allows organizations to shift from rigid monolithic architectures to flexible, scalable systems. Companies that update their applications are three times more likely to achieve a return on investment from their AI implementations compared to companies that do not.
How can organizations improve their application performance?
Teams can boost responsiveness through several methods: by optimizing code and databases, using dynamic load balancing, implementing a content delivery network (CDN) to cache content on distributed edge servers close to users, and adopting cloud-native architectures.